Title

Author

Date

2018

Document Type

Dissertation

Degree

Doctor of Philosophy

Department

Electrical Engineering

First Adviser

Kishore, Shalinee

Abstract

The presented research entails three critical areas of the electric power systems that can significantly impact its reliability and resiliency: retail market design (Chapters 2 - 4), renewable integration (Chapter 5) and post-disturbance grid recovery (Chapter 6).With the increase of intermittent renewable resource on the electric grid, comes the potential for more reliability issues. To increase reliability and efficient operation of the electric grid in presence of renewables, a novel retail electricity pricing scheme (GenMinimax) is introduced. The scheme incentivizes end-users to efficiently follow system operators/utilities optimal supply signals while shaping their demand for lower energy bills. The presentation will highlight the performance of GenMinimax compared to that of Time-of-Use and Real-time pricing. GenMinimax is preceded by Minimax pricing, which helps improve the load factor.Next, the work focuses on renewable market integration modeling. To increase renewable energy farms marketability and integration while interfacing the grid from the inherent volatility of their output, we devised optimal storage-based reliability-aware portfolio bidding strategies that enable them to participate in multiple markets and play an active role in grid reliability. A short-term reserve market was proposed and proved beneficial for both renewable farms and grid operation.The third solution area aims at devising post-disturbance restoration strategies for resilient power systems. For an efficient recovery after large disturbances such as weather-related power outages, a post-disaster microgrid formation model is proposed. The model applies to any type of network topology and accommodates demand-responsive loads and fixed or mobile distributed black-start resources for grid recovery operation and planning. A heuristic approach introduced, proves to reduce the CPU time.